Search form

NVIDIA Nsight Systems

NVIDIA® Nsight™ Systems is a system-wide performance analysis tool designed to visualize an application’s algorithms, help you identify the largest opportunities to optimize, and tune to scale efficiently across any quantity or size of CPUs and GPUs; from large server to our smallest SoC.

Overview

NVIDIA Nsight Systems is a low overhead performance analysis tool designed to provide insights developers need to optimize their software. Unbiased activity data is visualized within the tool to help users investigate bottlenecks, avoid inferring false-positives, and pursue optimizations with higher probability of performance gains. Users will be able to identify issues, such as GPU starvation, unnecessary GPU synchronization, insufficient CPU parallelizing, and even unexpectedly expensive algorithms across the CPUs and GPUs of their target platform. It is designed to scale across a wide range of NVIDIA platforms such as: large Tesla multi-GPU x86 servers, Quadro workstations, Optimus enabled laptops, DRIVE devices with Tegra+dGPU multi-OS, and Jetson. NVIDIA Nsight Systems can even provide valuable insight into the behaviors and load of deep learning frameworks such as PyTorch and TensorFlow; allowing users to tune their models and parameters to increase overall single or multi-GPU utilization.

What Users Are Saying

Tracxpoint

We noticed that our new Quadro P6000 server was ‘starved’ during training and we needed experts for supporting us. NVIDIA Nsight Systems helped us to achieve over 90 percent GPU utilization. A deep learning model that previously took 600 minutes to train, now takes only 90.

Felix Goldberg, Chief AI Scientist

NIH Center for Macromolecular Modeling and Bioinformatics at University of Illinois at Urbana-Champaign

Watch John Stone, present how he achieved over a 3x performance increase in VMD; a popular tool for analyzing large biomolecular systems.

Related Media

Watch John Stone, of the NIH Center for Macromolecular Modeling and Bioinformatics at University of Illinois at Urbana-Champaign, discuss how he achieved over a 3x performance increase of VMD, a popular tool for analyzing large biomolecular systems.

In the drone industry, the weight and size of the main board is critical. With the ZED stereo camera by Stereolabs, developers can capture the world in 3D and map 3D models of indoor and outdoor scenes up to 20 meters. The small form factor of the Jetson TX1 enables Stereolabs to bring advanced computer vision capabilities to smaller and smaller systems. See what is possible when these two technologies come together in drones to power the latest virtual reality applications.